Permutation - based statistical tests for multiple hypotheses

Background: Genomics and proteomics analyses regularly involve the simultaneous test of hundreds of hypotheses, either on numerical or categorical data. To correct for the occurrence of false positives, validation tests based on multiple testing correction, such as Bonferroni and Benjamini and Hochberg, and re-sampling, such as permutation tests, are frequently used. Despite the known power of permutation-based tests, most available tools offer such tests for either t-test or ANOVA only. Less attention has been given to tests for categorical data, such as the Chi-square. This project takes a first step by developing an open-source software tool, Ptest, that addresses the need to offer public software tools incorporating these and other statistical tests with options for correcting for multiple hypotheses. Results: This study developed a public-domain, user-friendly software whose purpose was twofold: first, to estimate test statistics for categorical and numerical data; and second, to...

• Type: Journal
• Year: 2008
• Where: SCFBM
• Authors: Anyela Camargo, Francisco Azuaje, Haiying Wang, Huiru Zheng
• Keywords: Categorical Data, Permutation Tests, SCFBM 2008, Test Statistic